The experiment results indicate that the welding-defect detection method based on semantic segmentation algorithm achieves 86.704% and the applicability of the proposed framework in industrial applications, which supports the effectiveness of the deep learning model in segmenting defects. As the main component of the new energy battery, the safety vent usually is welded …
The experiment results indicate that the welding-defect detection method based on semantic segmentation algorithm achieves 86.704% and the applicability of the proposed framework in industrial applications, which supports the effectiveness of the deep learning model in segmenting defects. As the main component of the new energy battery, the safety vent usually is welded …
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Hu et al proposed an effective model for detecting defects in lithium battery steel casings. The proposed model demonstrates superior overall performance with an average precision of …
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As the ownership of new energy vehicles (NEVs) is experiencing a sustained growth, the safety of NEVs has become increasingly prominent, with power battery faults emerging as the primary cause of fire accidents in NEVs. Successful detection of incipient faults can not only improve the safety and reliability but also provide optimal maintenance …
Multiple sensors are implemented to monitor the new energy battery, taking measurements of the battery pack''s voltage, current, and temperature, and estimating its State …
Fault detection of the electric vehicle battery system is vital for safe driving, energy economy, and lifetime extension. This paper proposes a data-driven method to achieve early and accurate ...
The methods of detection of internal SC and measurement of self-discharge have been discussed in literature for decades (1-9). However, for broad industry adoption, a method should be fast, accurate, non-destructive, and applicable to any cellchemistry or battery design. Recently, we proposed a new fast approach to the detection of Li-ion cell
Request PDF | Machine Learning-Enhanced Vision Systems for Cutting Tool Notch Detection in New Energy Battery Manufacturing | This paper presents a study on the problem of burrs on the electrodes ...
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With a swift detection time of 0.073 seconds per image, the model meets the stringent requirements for accuracy and real-time performance in identifying battery collector tray …
The future trend in global automobile development is electrification, and the current collector is an essential component of the battery in new energy vehicles. Aiming at the misjudgment and omission caused by the confusing distribution, a wide range of sizes and types, and ambiguity of target defec …
In order to reduce application costs and conduct real-time detection with limited computing resources, we propose an end-to-end adaptive and lightweight defect detection …
As an essential component of the new energy vehicle battery, current collectors affect the performance of battery and are crucial to the safety of passengers. The significant differences in shape and scale among defect types make it challenging for the model detection of current collector defects. In order to reduce application costs and conduct real-time detection with …
In this paper, due to the complexity of EVs'' battery thermal runaway tracing investigation and the limited capacity of on-board computing system, a double-layer fault …
In the proposed Lithium-ion battery Surface Defect Detection (LSDD) system, an augmented dataset of multi-scale patch samples generated from a small number of lithium-ion battery images is used in ...
As an essential component of the new energy vehicle battery, current collectors affect the performance of battery and are crucial to the safety of passengers. The significant differences in shape ...
As the main component of the new energy battery, the safety vent usually is welded on the battery plate, which can prevent unpredictable explosion accidents caused by the increasing internal pressure of the battery. The welding quality of safety vent directly affects the safety and stability of the battery; so, the welding-defect detection is of great significance. In …
Download Citation | On Jan 1, 2024, Sara Sepasiahooyi and others published Fault Detection of New and Aged Lithium-ion Battery Cells in Electric Vehicles | Find, read and cite all the research you ...
The FPS reaches 147.1, and the detection accuracy of various defect categories is improved, especially Severely bad and No cover, and the detection recall rate …
DGNet: An Adaptive Lightweight Defect Detection Model for New Energy Vehicle Battery Current Collector
We conduct a comprehensive study on a new task named power battery detection (PBD), which aims to localize the dense cathode and anode plates endpoints from X-ray images to evaluate the quality of power batteries. …
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Request PDF | Semantic segmentation supervised deep-learning algorithm for welding-defect detection of new energy batteries | As the main component of the new energy battery, the safety vent ...
Semantic segmentation supervised deep-learning algorithm for welding-defect detection of new energy batteries
for welding-defect detection of new energy batteries Yatao Yang1 • Yuqing He1 • Haolin Guo1 • Ziliang Chen1 • Li Zhang1 Received: 30 September 2021/Accepted: 26 May 2022/Published online: 25 June 2022 The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2022 Abstract As the main component of the new energy battery, the safety …
DOI: 10.25236/ajets.2023.060904 Corpus ID: 261499317; Battery voltage fault diagnosis mechanism of new energy vehicles based on electronic diagnosis technology @article{Sun2023BatteryVF, title={Battery voltage fault diagnosis mechanism of new energy vehicles based on electronic diagnosis technology}, author={Baowen Sun}, journal={Academic …
EOL automatic detection scheme for new energy vehicle battery system manufacturing process Yisong Chen1 & Haibo Xu1 & Shuru Liu1 Received: 12 March 2021/Accepted: 1 May 2021 # Saudi Society for Geosciences 2021 Abstract As we all know, compared with traditional fuel vehicles, new energy electric vehicles can not only save energy, but also reduce emissions, …
This paper introduces a new energy battery active-passive hybrid binocular intelligent inspection system, using structured light and laser line-scan instruments to acquire battery surface image information. Based on the existing 3D reconstruction technology, the active-passive hybrid binocular system is designed. In order to reduce the interference of multiple factors, the 3D …
1. Supports various battery pack diagnostic methods including non-standard battery pack connector, jumper cables and 16 PIN OBD. 2. Quick reading for battery pack information, such as number of battery pack modules, SOC, …
The continuous progress of society has deepened people''s emphasis on the new energy economy, and the importance of safety management for New Energy Vehicle Power Batteries (NEVPB) is also increasing (He et al. 2021).Among them, fault diagnosis of power batteries is a key focus of battery safety management, and many scholars have conducted …
In recent years, the new energy vehicle industry has developed rapidly. A fast diagnostic method based on Boosting and big data is proposed to address the low accuracy and efficiency of fault diagnosis in new energy vehicle power batteries. Boosting is a machine learning technique that combines multiple weak learners into a strong learner. Big data refers to large …
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